Cost-offset community supported agriculture (CO-CSA) appears to be a promising way to increase low-income households’ access and intake of fresh produce, while also helping CSA farms expand their farm business. Yet single farms operating CO-CSAs may struggle to balance the demands of farming with CO-CSA program administration, funding, and recruitment. To address these challenges, CO-CSA programs operated by nonprofits have emerged, equipped with dedicated infrastructure, resources, and staffing. This study aims to describe organizational models and best practices of nonprofit CO-CSA programs, using a qualitative approach. We conducted interviews with five well-established nonprofit CO-CSA programs in the U.S. Administration of these five nonprofit CO-CSAs took several forms: (1) providing direct subsidies to individual CO-CSA member farms; (2) functioning themselves as an aggregator, packer, and distributor of regional produce; and (3) sourcing from an in-house farm incubator or food hub, then packing and coordinating delivery to pick-up sites. Nonprofit CO-CSA funding strategies included grants from federal and local government sources, private donations, fundraising, and grants. Marketing efforts occurred via social media, community events, and word of mouth. Both fundraising and recruitment were greatly facilitated by relationships with community partners. Having dedicated staff, as well as a community that values local agriculture and social justice, were identified as success factors. This descriptive, qualitative study systematically compares the attributes of five nonprofit CO-CSA programs. Future research should focus on identifying the cost-effectiveness of nonprofit CO-CSAs, compare the relative merits of single-farm and nonprofit CO-CSAs, and quantify the economic benefit of CO-CSA programs for farmers and local communities.
To improve low-income families’ access to fresh local produce, some farmers offer subsidized or “cost-offset” community supported agriculture (CO-CSA) shares. We evaluated a structured planning and implementation process conducted during the final intervention year of the Farm Fresh Foods for Healthy Kids (F3HK) study, which aimed to help participating farmers (N=12) to sustain a CO-CSA program after study funding ended. The process included training webinars, planning tools to develop CO-CSA continuation funding and recruitment strategies, regional coaching teams to provide technical assistance, and periodic group conference calls to facilitate shared learning among F3HK farmers. Our evaluation explored the content of farmers’ CO-CSA continuation plans, their experiences during implementation, their opinions about the planning process, and their future plans regarding their CO-CSA. We found that F3HK farmers used diverse methods to plan, recruit, and raise funds, with each farm adapting strategies to fit their local conditions and farm business. Many farmers found success with word-of-mouth advertising and CSA member donations. Yet lack of farm resources—time, money, and expertise—was a continual barrier to moving forward. As with full price CSAs, reciprocity was a key factor: farmers needed to consider the needs and preferences of low-income consumers, and CO-CSA members needed to understand their financial responsibility to the farmer. In general, F3HK farmers appreciated the continuation planning process, but expressed a desire for more technical assistance with grant writing. Farmers were committed to the success of the CO-CSA continuation planning process, and most intended to continue the CO-CSA the following year.
Some farmers are offering subsidized or “cost-offset” community supported agriculture (CO-CSA) shares as a strategy to counter market saturation and improve low-income families’ access to fresh local foods. However, little is known about farmers’ experiences with this model, particularly in regard to the balance between additional resources required for adoption and subsequent contributions to farm revenue. As part of the Farm Fresh Foods for Healthy Kids Study of the impact of a CO-CSA on dietary behaviors in low-income families, we conducted qualitative interviews with 12 farmers across four states after the first and the third years of CO-CSA implementation. We explored these data to understand what accommodations farmers provided to low-income families, the benefits and challenges of implementing the CO-CSA model, and farmers’ perceptions of its impact on cash flow and profitability. We found that farmers selected pick-up locations that met CO-CSA members’ needs, were responsive to members’ food preferences in selecting CSA contents, and allowed for late payments and pickups, though sometimes this placed an additional burden on farmers’ time and resources. Additionally, weekly payment transactions led to increased recordkeeping. Despite its challenges, most farmers said CO-CSA adoption was a worthwhile addition to their business model. Expanding food access through this mechanism may become more sustainable with the additional support of innovative policies like eased land-use restrictions, operational models, and community strategies to fund and operate CO-CSA programs. This is an area ripe for future research, as there is little documentation on both single farm and multifarm CO-CSA operations.
Malnutrition is a common problem in geriatric patients that often goes unrecognized. Undernutrition is a primary health concern for older adults due to associations with increased mortality, complications, and length of hospital stay. Yet, there is no consensus on which malnutrition screening tool should be used for hospitalized older adults. Therefore, the objective of this study was to determine which screening tool is best to rapidly detect malnutrition in hospitalized older adults so that patient outcomes may be improved. Older adult patients (n = 211; ≥65 yrs old) were enrolled during acute hospitalization. Testing occurring within 72 hours of admission and included the following screening tools included: Malnutrition Screening Tool (MST), Mini Nutritional Assessment Short Form (MNA-SF), Malnutrition Universal Screening Tool (MUST), Nutrition Risk Screening 2002 (NRS-2002), and Geriatric Nutritional Risk Index (GNRI). These screening tools were compared to a malnutrition diagnostic tool, the Subjective Global Assessment (SGA). According to SGA, 49% of patients were at risk of being malnourished. The other screening tools indicated a wide range of malnutrition prevalence, from 18% (MST) to 76% (MNA-SF). MST (93%) and MUST (92%) were highest in sensitivity. NRS-2002 had moderately good sensitivity (71%). MNA-SF and GNRI had poor sensitivity, eliminating them as good screening tools for hospitalized elderly patients. Of the remaining tools, NRS-2002 had the highest specificity (77%). MST and MUST had poor specificity (31%, 39%, respectively), eliminating them as good screening tools for hospitalized elderly patients. The remaining screening tool, NRS-2002, had moderately good positive and negative predictive values (76%, 72%, respectively). It also had the highest kappa (0.479). Overall, NRS-2002 had the best agreement to SGA and showed moderately good sensitivity, specificity and predictive values. Our data suggests NRS-2002 is the best malnutrition screening tool for rapid detection of malnutrition in elderly hospitalized patients, when compared to the diagnostic tool, SGA. Future research is needed to determine which screening tool is most effective for use in different settings. Additional research can assist in standardizing malnutrition criteria and care processes. National Dairy Council, National Institutes of Health-National Center for Advancing Translational Sciences, and UTMB Claude D. Pepper OAIC.